IrisAgent vs Decagon: No-Code AI Support That Ships in 24 Hours
Decagon requires developers, code-based AOPs,
and 6 weeks of implementation. IrisAgent is fully
no-code — your support team owns the AI, live in
under 24 hours with 95%+ accuracy.
and 6 weeks of implementation. IrisAgent is fully
no-code — your support team owns the AI, live in
under 24 hours with 95%+ accuracy.
Decagon requires developers, code-based AOPs, and 6 weeks of implementation. IrisAgent is fully no-code — your support team owns the AI, live in under 24 hours with 95%+ accuracy.
Why support teams choose IrisAgent over Decagon
Your support team should own the AI — not depend on engineering sprints
Fastest Time to Value
Go live in under 24 hours with no engineering resources. Decagon's implementation takes 6 weeks minimum.
24 hrsavg. deployment
Fully No-Code
No developers, no Git, no Agent Operating Procedures. Your support team configures everything visually.
0lines of code
Hallucination-Free AI
Proprietary Hallucination Removal Engine validates every response. No made-up answers — ever.
95%+accuracy rate
Built-in Agent Copilot
Real-time AI assist for human agents with proactive suggestions. Not just full automation or nothing.
2xagent efficiency
IrisAgent vs Decagon: Feature-by-feature comparison
 | Decagon | |
|---|---|---|
| Target Market & Accessibility |  Designed for mid-market and enterprise teams — transparent pricing accessible to growing companies No minimum contract thresholds — start small and scale as you see results |  Enterprise-only focus with minimum platform fees starting at ~$50,000+/year Typical annual contracts range $300,000–$500,000+ — inaccessible for mid-market teams |
| AI Architecture | Multi-agent system with specialized AI for email, chat, voice, and copilot — all coordinating together Configurable LLM federation with OpenAI, Anthropic, Azure, and more | Single generalist AI agent handling all issue types — can struggle with multi-topic conversations Agent Operating Procedures (AOPs) require code and developer involvement to configure |
| Pricing Model | Transparent, predictable pricing accessible to mid-market teams AI capabilities included — not metered or usage-gated | Custom pricing with per-conversation or per-resolution models — no public pricing Median annual contracts around $386,000 with minimums starting at ~$50,000+ |
| Setup Complexity | Fully no-code — any support leader can configure workflows, tone, and responses Go live in under 24 hours without writing a single line of code | 6-week implementation process: discovery, AOP development, testing, and controlled rollout Agent Operating Procedures require code-level configuration and developer resources |
| AI Accuracy & Hallucinations | 95%+ accuracy with proprietary Hallucination Removal Engine Every response validated against your knowledge base and real support data before delivery | Black-box concerns — users report difficulty understanding why AI made specific decisions No proprietary hallucination elimination technology |
| Technical Requirements | Zero technical requirements — designed for support teams, not engineering teams No Git, no code reviews, no developer sprints needed to manage AI behavior | Requires developers to write and maintain Agent Operating Procedures Uses Git version control for AOP management — assumes engineering team involvement |
| AI Copilot for Agents | Built-in AI copilot with real-time resolution suggestions, response guidance, and summarization Proactive recommendations powered by similar tickets and bug data | Focused on full automation — limited built-in support for human agent augmentation Agent assist capabilities secondary to autonomous resolution |
| Trending Incidents & Proactive Insights | Automatically discover trending topics and get proactive alerts on emerging issues Real-time escalation prediction using customer health, sentiment, and revenue signals | Watchtower monitoring for AI performance, but limited proactive support insights No trending incident detection or automatic alerting on emerging customer issues |
| Sentiment & Escalation Analysis | AI-powered, granular sentiment analysis measured per ticket with escalation prediction | Basic escalation handling — lacks deep sentiment analysis and predictive escalation |
No-code AI that your support team actually owns
Decagon's Agent Operating Procedures require developers to write code, manage Git repositories, and run through engineering review cycles. IrisAgent gives your support team full control with a no-code interface — configure workflows, adjust tone, and manage AI responses without filing a single engineering ticket.
Live in 24 hours — not 6 weeks
Decagon follows a 6-week implementation cycle: discovery, AOP development, configuration, integration testing, and controlled rollout. IrisAgent deploys in under 24 hours — connect your helpdesk, let the AI train on your data, and start automating. No week-by-week project plans required.
AI copilot for agents — not just full automation
Decagon focuses on fully autonomous resolution, leaving human agents without AI guidance when tickets are escalated. IrisAgent's built-in copilot provides real-time resolution suggestions, response guidance, and ticket summarization — empowering your agents to handle complex issues faster, not just deflecting the easy ones.
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